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Record W3017257257 · doi:10.1215/00382876-8177735

Ǧviḷás and Snəwayəɬ: Indigenous Laws, Economies, and Relationships with Place Speaking to State Extractions

2020· article· en· W3017257257 on OpenAlexaboutno aff
Deborah Curran, Eugene Kung, Ǧáǧvi Marilyn Slett

Bibliographic record

VenueSouth Atlantic Quarterly · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousJurisdictionState (computer science)Political scienceAotearoaIndigenous rightsCorporate governanceEconomyLawHuman rightsEcologyEconomicsManagement

Abstract

fetched live from OpenAlex

A discussion about Indigenous economies, governance, and laws begins with relationships. These relationships are centered in a place, a traditional territory, and include responsibilities towards that place. Such a relational approach to Indigenous economies is in conflict with capitalist modes of extraction and the settler Canadian court’s narrow conception of the duties of “consultation and accommodation” as the state’s primary responsibility when an activity or project will infringe Aboriginal rights in a traditional territory. The purpose of this article is to explore the conflict between Indigenous economies and state-sponsored extraction drawing on the experience of two Indigenous nations in British Columbia, Canada—the Heiltsuk and Tsleil-Waututh Nations—who are upholding their relationship with their traditional territories through the assertion of jurisdiction. The Heiltsuk continue to challenge the federal Department of Fisheries and Oceans’ permitting commercial herring fisheries, and have dealt with a marine diesel spill using their own legal processes. The Tsleil-Waututh are opposing the construction of another fossil fuel pipeline in their territory that would increase tanker traffic in the habitat of endangered orcas by seven hundred percent by conducting their own assessment of the project based on Coast Salish law. These exercises of jurisdiction demonstrate relations with and responsibilities towards these Nations’ traditional territories that underscore ecosystem health and wellbeing as the foundation of Indigenous economies. While these examples effectively demonstrate the Nations’ responsibility towards their territories, the regimes of state-sponsored extractions require radical reformulation to be able to engage relational processes of consent.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.529
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.179
Teacher spread0.165 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2020
Admission routes1
Has abstractyes

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